With the spread of smartphones and the continuous development of SNSs (Social Network Services), an increasing attention is paid to a variety of image search and augmented reality services using local descriptors on a basis of interest points.
A technology for extracting invariant interest points is a requisite for the provision of the image search and augmented reality services. There has been proposed various techniques for extracting the interest points. Among of them, an interest point detector using DoG (Different of Gaussian) is most commonly used, which may be employed in SIFT (Scale-Invariant Feature Transform) (see, D. Lowe, “Distinctive image features from scale-Invariant key points,” Int. J. Comput. Vis, vol 60, no 2, pp 91.110, 2004). The DoG uses difference image using Gaussian image as an approximation value of the LoG (Laplacian of Gaussian), which has an advantage in terms of an amount of computation.
However, the interest point detector has disadvantages in that it not only requires an additional storage space for Gaussian images and difference images, but also has no choice to use an approximation of the LoG.